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Found 4 papers, 2 papers with code
The Weak Supervision Landscape
In this paper we propose a framework for categorising weak supervision settings with the aim of: (1) helping the dataset owner or annotator navigate through the available options within weak supervision when prescribing an annotation process, and (2) describing existing annotations for a dataset to machine learning practitioners so that we allow them to understand the implications for the learning process.
Classifier Calibration: A survey on how to assess and improve predicted class probabilities
This paper provides both an introduction to and a detailed overview of the principles and practice of classifier calibration.
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration
Class probabilities predicted by most multiclass classifiers are uncalibrated, often tending towards over-confidence.
HyperStream: a Workflow Engine for Streaming Data
This paper describes HyperStream, a large-scale, flexible and robust software package, written in the Python language, for processing streaming data with workflow creation capabilities.
